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Record W2099319927 · doi:10.1162/leon.2010.43.3.274

Blending Art and Science: <i>Collapse (suddenly falling down)</i>

2010· article· en· W2099319927 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLeonardo · 2010
Typearticle
Languageen
FieldComputer Science
TopicComputer Graphics and Visualization Techniques
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsFalling (accident)Theme (computing)Natural (archaeology)Perspective (graphical)Visual artsDanceSociologyAestheticsComputer scienceArtHistoryPsychologyWorld Wide Web

Abstract

fetched live from OpenAlex

Collapse (suddenly falling down) was a dance/theater/media production that brought together a diverse group of artists and scientists to explore the varied ways that social and natural systems collapse and the responses of human societies. This paper focuses on the nature of the collaboration, the unique products it produced and the lessons learned. Three art-science collaboration themes emerged: (1) implementation of a large-scale stereo display for 3D data; (2) exploration from a visual design perspective of digital scans of natural hazard sites normally used for scientific research; and (3) integration of optical tracking for interaction between performers and visualizations. Each theme is explored in detail and each member of the team reflects on lessons learned from the process.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.838
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.275
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it